Development of an Object Tracking and Classification Program on a Robotic Conveyor Line

An algorithm for classifying and tracking the object has been developed. The algorithm is based on the use of the YOLOv5 neural network for high-precision classification of objects in real time. The developed software implementation of the algorithm is based on the Python programming language and the OpenCV library. During the work, the program was debugged and optimized to improve the performance and accuracy of the system. The evaluation of the technical solution showed that the developed system significantly improves the accuracy and speed of data processing on the conveyor line, as well as provides adaptability to changes in the production process.